Skip to main content
Log in

A Proportioning Based Algorithm with Rate of Convergence for Bound Constrained Quadratic Programming

  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

The proportioning algorithm with projections turned out to be an efficient algorithm for iterative solution of large quadratic programming problems with simple bounds and box constraints. Important features of this active set based algorithm are the adaptive precision control in the solution of auxiliary linear problems and capability to add or remove many indices from the active set in one step. In this paper a modification of the algorithm is presented that enables to find its rate of convergence in terms of the spectral condition number of the Hessian matrix and avoid any backtracking. The modified algorithm is shown to preserve the finite termination property of the original algorithm for problems that are not dual degenerate.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. O. Axelsson, Iterative Solution Methods (Cambridge Univ. Press, Cambridge, 1994).

    Google Scholar 

  2. M.S. Bazaraa and C.M. Shetty, Nonlinear Programming (Wiley, New York, 1979).

    Google Scholar 

  3. R.H. Bielschowski, A. Friedlander, F.A.M. Gomes, J.M. Martínez and M. Raydan, An adaptive algorithm for bound constrained quadratic minimization, Investigacion Operativa 7 (1997) 67–102.

    Google Scholar 

  4. P.H. Calamai and J.J. Moré, Projected gradient methods for linearly constrained problems, Math. Programming 39 (1987) 93–116.

    Google Scholar 

  5. T.F. Coleman and L.A. Hulbert, A globally and superlinearly convergent algorithm for convex quadratic programs with simple bounds, SIAM J. Optim. 3(2) (1993) 298–321.

    Google Scholar 

  6. M.A. Diniz-Ehrhardt, Z. Dostál, M.A. Gomes-Ruggiero, J.M. Martínez and S.A. Santos, Non-monotone strategy for minimization of quadratics with simple constraints, Appl. Math. 46(5) (2001) 321–338.

    Google Scholar 

  7. M.A. Diniz-Ehrhardt, M.A. Gomes-Ruggiero and S.A. Santos, Numerical analysis of the leaving-face criterion in bound-constrained quadratic minimization, Optim. Methods Software 15 (2001) 45–66.

    Google Scholar 

  8. Z. Dostál, Box constrained quadratic programming with proportioning and projections, SIAM J. Optim. 7(3) (1997) 871–887.

    Google Scholar 

  9. Z. Dostál, Inexact solution of auxiliary problems in Polyak type algorithms, Acta Univ. Palacki. Olomuc., Fac. Rer. Nat., Mathematica 38 (1999) 25–30.

    Google Scholar 

  10. Z. Dostál, A. Friedlander and S.A. Santos, Adaptive precision control in quadratic programming with simple bounds and/or equalities, in: High Performance Software for Nonlinear Optimization, eds. R. De Leone, A. Murli, P.M. Pardalos and G. Toraldo, Applied Optimization 24 (1998) 161–173.

  11. Z. Dostál, F.A.M. Gomes and S.A. Santos, Duality based domain decomposition with natural coarse space for variational inequalities, J. Comput. Appl. Math. 126(1/2) (2000) 397–415.

    Google Scholar 

  12. Z. Dostál, F.A.M. Gomes and S.A. Santos, Solution of contact problems by FETI domain decomposition with natural coarse space projection, Comput. Methods Appl. Mech. Engrg. 190(13/14) (2000) 1611–1627.

    Google Scholar 

  13. Z. Dostál, F.A.M. Gomes and S.A. Santos, Duality based domain decomposition with natural coarse space for variational inequalities, J. Comput. Appl. Math. 126(1/2) (2000) 397–415.

    Google Scholar 

  14. Z. Dostál and D. Horák, Scalability and FETI based algorithm for large discretized variational inequalities, Math. Comput. Simulation 61(3–6) (2003) 347–357.

    Google Scholar 

  15. A. Friedlander and M. Martínez, On the maximization of a concave quadratic function with box constraints, SIAM J. Optim. 4 (1994) 177–192.

    Google Scholar 

  16. A. Friedlander, J.M. Martínez and S.A. Santos, A new trust region algorithm for bound constrained minimization, Appl. Math. Optim. 30 (1994) 235–266.

    Google Scholar 

  17. A. Friedlander, J.M. Martínez and M. Raydan, A new method for large scale box constrained quadratic minimization problems, Optim. Methods Software 5 (1995) 57–74.

    Google Scholar 

  18. J.J. Moré and G. Toraldo, On the solution of large quadratic programming problems with bound constraints, SIAM J. Optim. 1 (1991) 93–113.

    Google Scholar 

  19. D.P. O'Leary, A generalised conjugate gradient algorithm for solving a class of quadratic programming problems, Linear Algebra Appl. 34 (1980) 371–399.

    Google Scholar 

  20. B.T. Polyak, The conjugate gradient method in extremal problems, USSR Comput. Math. Math. Phys. 9 (1969) 94–112.

    Google Scholar 

  21. J. Schöberl, Solving the Signorini problem on the basis of domain decomposition techniques, Computing 60(4) (1998) 323–344.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dostál, Z. A Proportioning Based Algorithm with Rate of Convergence for Bound Constrained Quadratic Programming. Numerical Algorithms 34, 293–302 (2003). https://doi.org/10.1023/B:NUMA.0000005347.98806.b2

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:NUMA.0000005347.98806.b2

Navigation